The Spatial–Temporal Changes of the Coupling Relationship Among Agricultural Labor Force, Agricultural Economy, and Farmland in Chongqing

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Article The Spatial–Temporal Changes of the Coupling Relationship among Agricultural Labor Force, Agricultural Economy, and Farmland in Chongqing

Lin Zhu 1,*, Mingying Yang 2, Wenzhuo Li 1, Heping Liao 2 and Han Huang 2

1 College of State Governance, Southwest University, Chongqing 400700, China; [email protected] 2 School of Geographical Sciences, Southwest University, Chongqing 400700, China; [email protected] (M.Y.); [email protected] (H.L.); [email protected] (H.H.) * Correspondence: [email protected]; Tel.: +86-(15)-17-887-6878

Abstract: Agricultural labor force, agricultural economy, and farmland use are momentous com- ponents of sustainable development in rural areas, as well as essential causes of drastic changes in the urban–rural transformation. This paper studies the spatial–temporal characteristics of the labor–farmland–economy coupling structure from 2000 to 2018 in rural areas of Chongqing using spatial analysis technology. The study has four main results. First and foremost, not only has the average annual rate of the agricultural labor force in Chongqing reduced by 3.73%, but the reduction

rates in Jiangbei District, Dadukou District, Nan’an District, Shapingba District, and Yubei District have exceeded 15%. Then, the average annual rate of the agricultural economy has increased by

Citation: Zhu, L.; Yang, M.; Li, W.; 9.32%, but it has been in a downward trend in Dadukou District, Jiangbei District, and Shapingba Liao, H.; Huang, H. The Districts. Furthermore, the average annual decline rate of farmland area is 0.34% with larger re- Spatial–Temporal Changes of the duction occurring in the nine of the central urban districts, Chengkou County and Wushan County. Coupling Relationship among Ultimately, there have been 33 districts and counties with the temporal–spatial characteristics of Agricultural Labor Force, labor–farmland–economy coupling above primary coordination, which includes 16 districts and Agricultural Economy, and Farmland counties reaching a high coordination. This provides theoretical and methodical supports for the in Chongqing. Sustainability 2021, 13, coordinated development of human and land industries in different regions. 8780. https://doi.org/10.3390/su 13168780 Keywords: agricultural labor force; agricultural economy; farmland change; urbanization; rural revitalization Academic Editors: Changhe Lu and Wenjiao Shi

Received: 5 June 2021 1. Introduction Accepted: 27 July 2021 Published: 5 August 2021 Agriculture serves as a prerequisite for the survival and advancement of humankind and plays a unique role in the economic society. It is quite valuable for rural areas in

Publisher’s Note: MDPI stays neutral agricultural production and ecological conservation; issues related to farmers, agriculture, with regard to jurisdictional claims in and rural areas are fundamental to the national economy and people’s livelihoods, and published maps and institutional affil- agricultural and rural modernization forms the foundation for a modern country [1]. iations. During the period of rapid industrialization and urbanization, labor, land, capital, and other factors of production continue to gather in cities [2]; the income disparity between the agricultural sector and the non-agricultural sector has widened, and the income structure of farmers is undergoing significant changes [3]. All aspects of gap between urban areas and rural areas in China have been widened, and the income ratio between the two areas has Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. expanded from 2.57 in 1978 to 2.72 in 2016. The “rural diseases”—older and weaker people This article is an open access article forming most of the population, a poor economy, vacant and waste land, and environmental distributed under the terms and pollution—have become increasingly serious, resulting in the rapid recession of agriculture conditions of the Creative Commons and rural areas [4]. Attribution (CC BY) license (https:// Population, land, and industry are three main factors of the urban–rural system, creativecommons.org/licenses/by/ as well as important indicators that reflect the urban–rural transformation and develop- 4.0/). ment [5]. With the continuous reduction in agricultural benefits and the rapid increase

Sustainability 2021, 13, 8780. https://doi.org/10.3390/su13168780 https://www.mdpi.com/journal/sustainability Sustainability 2021, 13, 8780 2 of 17

in wages and income in the non-agricultural industry [6], the large-scale outflow of rural young and middle-aged populations lead to a “hollowing” in rural areas, with only “old and weak” residents been left behind. This, in turn, causes the dilemmas of empty homesteads, abandoned farmland, slow agricultural development, and low benefits, as well as significant changes to rural land use [7]. Since the beginning of the 21st century, the imbalance between population and land in urbanization has gradually been expanded [8], and the proportion of the added value of agriculture, forestry, animal husbandry, side-line production, and fishery in the national GDP has decreased [9]. Therefore, more attention should be paid to rural revitalization in the process of rapid urbanization [10]. The coupling coordination of agricultural labor force, agricultural economy, and land is the key to the sustainable development of rural areas. The revitalization of population, industry, and land forms the basis for activating the rural vitality and enhancing development capability [11]. The transfer of agricultural surplus labor will improve agricultural efficiency [12]; economic policy reform, science, and technology progress will enhance agricultural production efficiency and benefits, thus, reducing employment opportunities for agricultural labor [13]. The migration of the agricultural labor force to non-agricultural sectors is helpful to land transfers [14], increasing farmers’ income, and, thus, promoting the development of the agricultural economy [15]. It has been shown that when the transfer of agricultural labor exceeds a critical value, it promotes the transfer of agricultural land and scale management [16]; however, with the increase in labor transfer, agricultural production is affected negatively. The excessive outflow of agricultural labor force will accelerate the aging of the old and reduce land revenue [17], thus, resulting in the decrease in farmland use intensity [7] and the acceleration of farmland abandonment [18]. To sum up the previous studies, an adaptive level of labor transfer is an effective means to promote a sustainable economy. Labor force is a crucial factor restricting the development of rural industries. On the one hand, the excessive outflow and decrease in labor force have a more negative influence on the sustainable development with population aging, farmland abandonment, and village hollowing. [19]. Due to the scarcity of a young and middle-aged labor force, as well as the decline of human capital, the effect of cultivated land on the population agglom- eration in mountainous areas has weakened [20]; the labor cost of industrial development continues to rise, which squeezes the benefits of agricultural industry and seriously does not motivate the development of secondary and tertiary industries [21]. On the other hand, the introduction of high-quality talents in rural areas is insufficient. Under the background of rural revitalization, industrial development is gradually moving toward a large-scale intensification and modernization. Furthermore, management talents of rural skilled labor force are scarcer. The transferred agricultural labor force is mostly composed of the higher education population, but the weak labor force stays in rural areas [22], showing a serious imbalance between the outflow of labor and introduction of labor. It is difficult to maintain the labor security of agricultural modernization, resulting in difficulties in improving the output efficiency of agricultural land, which has not fully activated the role of rural labor in the intensive use of land for industrial development. It is not conducive to the sustainable development of agricultural production [23], and farmers and policy makers must deal with the current labor challenge [24]. The 38 counties of the Chongqing Municipality are grouped into the following cat- egories: central city, new districts of the main city, Northeast Chongqing, and Southeast Chongqing, which consist of 9, 12, 11, and 6 counties, respectively. These groupings are determined based on the geographical location and the economic and cultural conditions of the counties and in combination with the construction plan of Chongqing’s main urban areas in 2020 (Figure1). Sustainability 2021, 13, 8780 3 of 17 Sustainability 2021, 13, x 3 of 16

FigureFigure 1. 1.Administrative Administrative division division map map of of the the study study site. site.

2.2. RelationshipRelationship amongamong AgriculturalAgricultural Labor,Labor, Agricultural Agricultural Economy, Economy, and and Farmland Farmland 2.1.2.1. InteractionInteraction betweenbetween AgriculturalAgricultural LaborLabor Transfer Transfer and and Farmland Farmland Use Use AA reasonable reasonable transfer transfer of of agricultural agricultural labor labor force force will will be conducivebe conducive to the to intensivethe intensive use ofuse farmland, of farmland, while while an unreasonablean unreasonable transfer transfer will will lead lead to to the the inefficient inefficient use use of of farmland farmland (Figure(Figure1 ).1). The The tension tension between between humans humans and and land land has has become become prominent prominent in in China; China; at at the the same time, the shortage and fragmentation of farmland resources restrict the large-scale same time, the shortage and fragmentation of farmland resources restrict the large-scale agricultural operation [25]. The transfer of agricultural labor force helps not only alleviate agricultural operation [25]. The transfer of agricultural labor force helps not only alleviate the contradiction between rural people and land, promote the transfer of farmland and the contradiction between rural people and land, promote the transfer of farmland and the large-scale management, facilitate the application of modern agricultural advanced the large-scale management, facilitate the application of modern agricultural advanced technology and machinery, but also improve the output rate of farmland and agricultural technology and machinery, but also improve the output rate of farmland and agricultural benefits [26,27]. Unreasonable labor transfer will lead to the abandonment of some farm- benefits [26,27]. Unreasonable labor transfer will lead to the abandonment of some farmland without cultivation and the cultivated farmland will shrink in production capacity and land without cultivation and the cultivated farmland will shrink in production capacity benefits due to the decrease in input of the agricultural means of production and manage- and benefits due to the decrease in input of the agricultural means of production and ment of time [7,28]. Farmland use also affects labor transfers (Figure1) since the intensive management of time [7,28]. Farmland use also affects labor transfers (Figure 1) since the use of farmland and the capacity improvement can effectively liberate the labor force, increaseintensive the use demand of farmland for agricultural and the capacity labor force,improvement and promote can effectively non-agricultural liberate employ-the labor mentforce, [ 29increase]; despite the of demand a surplus for of agricultural rural labor la force,bor force, the fragmented and promote farmland non-agricultural management em- retainsployment more [29]; labor despite force of [30 a]; su thus,rplus limiting of rural the labor transfer force, ofthe labor fragmented force. farmland manage- mentConclusively, retains more thelabor transfer force [30]; of agricultural thus, limiting labor the forcetransfer is closely of labor related force. to the devel- opmentConclusively, of the agricultural the transfer economy of agricultural and land la use,bor which force is is closely an essential related element to the develop- of rural revitalization.ment of the agricultural However, the economy current studiesand land focus use, on which discussing is an theessential unilateral element influence of rural of regionalrevitalization. agricultural However, labor the force current on the studies agricultural focus economyon discussing or that the of unilateral agricultural influence labor forceof regional on farmland agricultural use, lack labor of force research on the on agri the couplingcultural economy relationship or that among of agricultural agricultural la- laborbor force force, on agricultural farmland use, economy, lack of and research farmland. on the coupling relationship among agricultural labor force, agricultural economy, and farmland. 2.2. Interaction between Agricultural Labor Transfer and Development of Agricultural Economy 2.2. InteractionThe appropriate between transfer Agricultural of agricultural Labor Transfer labor and force Development will promote of Agricultural the development Economy of theThe agricultural appropriate economy, transfer while of agricultural too much orlabor too force little will transfer promote will leadthe development to a low-level of developmentthe agricultural of theeconomy, agricultural while economy too much (Figure or too2 ).little A suitable transfer labor will lead transfer to a will low-level help farmersdevelopment acquire of new the skills,agricultural improve economy the quality (Figur of thee 2). labor A suitable force, promote labor transfer the application will help farmers acquire new skills, improve the quality of the labor force, promote the application SustainabilitySustainability2021 2021,,13 13,, 8780 x 44 of 1716

ofof agriculturalagricultural technologies, advance agriculturalagricultural production efﬁciency,efficiency, andand boostboost the de- velopmentvelopment ofof the the agricultural agricultural economy economy [31 ,[31,32].32]. In addition,In addition, the transferthe transfer of agricultural of agricultural labor forcelabor canforce promote can promote the optimal the optimal allocation allocation of rural of resources rural resources among industries among industries and promote and large-scalepromote large-scale agricultural agricultural operation operation [33]. On the [33] one. On hand, the givenone hand, the fact given that the the fact young that and the middle-agedyoung and middle-aged (or high-quality) (or high-quality) population formspopulation the chunk forms of the the chunk transferred of the labortransferred force, anylabor excessive force, any transfer excessive oflabor transfer force of willlabor lead force to will the shortagelead to the of shortage rural human of rural resources, human andresources, agricultural and agricultural production willproduction have to will be operated have to mainlybe operated by old-aged mainly and by old-aged weak people. and Asweak a result, people. agricultural As a result, development agricultural and development the rural economy and the willrural be economy obstructed will [34 be]. Onob- thestructed other [34]. hand, On the the development other hand, ofthe the development agricultural of economy the agricultural will promote economy or restrict will pro- the transfermote or ofrestrict the agricultural the transfer labor of the force agricultural (Figure2 ).labor A heightened force (Figure agricultural 2). A heightened economy agri- is conducivecultural economy to the prosperity is conducive of industries to the prosperity in rural areasof industries [35]. As in the rural agricultural areas [35]. industry As the continuesagricultural to industry grow and continues the industrial to grow chain and of the agricultural industrial productschain of agricultural extends, agriculture products willextends, provide agriculture more jobs will and provide a higher more income jobs for and rural a higher residents, income and for promote rural theresidents, transfer and of thepromote agricultural the transfer labor of force the agricultural and social development. labor force and However, social development. the lack of motivation However, forthe thelack development of motivation of for the the agricultural development economy of the will agricultural reduce the economy employment will reduce opportunities the em- andployment income opportunities of the labor forceand income and reduce of the the labor ﬂow force of population, and reduce land,the flow and of other population, factors. Thisland, will and eventually other factors. cause This such will problems eventually as the cause gradual such depressionproblems as of the the gradual social economy depres- andsion regionalof the social poverty. economy and regional poverty.

FigureFigure 2.2. FrameworkFramework betweenbetween agriculturalagricultural laborlabor transfer,transfer, agriculturalagricultural economiceconomic development,development, andand farmlandfarmland use.use.

3.3. Materials and MethodsMethods 3.1. Data Source 3.1. Data Source Located in the west of China, Chongqing has 38 counties (districts or county-level Located in the west of China, Chongqing has 38 counties (districts or county-level cities, same below). Since there is no rural population in Yuzhong District, Chongqing, it cities, same below). Since there is no rural population in Yuzhong District, Chongqing, it has not been included in this study. Its rural population is large in size, with a low-level has not been included in this study. Its rural population is large in size, with a low-level farmland area per capita. Consequently, it faces such problems as a high-outflow rate of farmland area per capita. Consequently, it faces such problems as a high-outflow rate of the agricultural population and the aging of the population, and its rural development is the agricultural population and the aging of the population, and its rural development is at a medium level [36]. Land fragmentation reduces agricultural labor productivity and at a medium level [36]. Land fragmentation reduces agricultural labor productivity and production efficiency; thus, indirectly driving the transfer of agricultural labor to the non- production efficiency; thus, indirectly driving the transfer of agricultural labor to the non- agricultural sectors [25]. Previous studies have shown that the transfer of the agricultural agricultural sectors [25]. Previous studies have shown that the transfer of the agricultural labor force in Chongqing had produced significant effects in economic growth, agricultural labor force in Chongqing had produced significant effects in economic growth, agricul- output, and agricultural income, which provided solid support for the overall planning of bothtural itsoutput, urban and and agricultural rural areas[ income,37]. Some which other provided studies show solid that support the transfer for the ofoverall rural laborplan- forcening inof Chongqingboth its urban has and only rural increased areas farmers’ [37]. Some income, other but studies has not show significantly that the transfer improved of therural city’s labor agricultural force in Chongqing output [38 ].has Since only the increased launching farmers’ of the targetedincome, povertybut has alleviationnot signifi- campaign,cantly improved significant the city’s changes agricultural have taken output place [38]. in population, Since the launching land use, and of the industry targeted in Sustainability 2021, 13, 8780 5 of 17

rural areas. It is urgent to conduct research on the coupling relationship among agricultural labor force, rural economy, and farmland changes in Chongqing. This research will support policy making for consolidating and expanding the achievements of poverty alleviation, and promote rural revitalization and urban–rural integration and development. Therefore, the main contents of this study are as follows: (1) constructing a logical framework of agricultural labor transfer, agricultural economy, and farmland use; (2) analyzing the temporal–spatial change of rural labor force, development of agricultural economy, and farmland in Chongqing; (3) explaining the temporal–spatial coupling characteristics of the labor–farmland–economy structure in Chongqing and the formation mechanism. The data in this study include the number of agricultural workers and the total output value of the agricultural economy and farmland from 2000 to 2017. These data came from the Chongqing Statistical Yearbook and the data of the stated counties. Some missing data were supplemented by the linear interpolation formula or the mean difference compensation method, in combination with the data as released in the government work reports of the counties. In addition, to make the data of different years comparable, this paper ignored the inﬂuence of price changes.

3.2. Research Methods 3.2.1. Labor–Farmland Elastic Coefﬁcient Using the Labor–Farmland Elastic Coefﬁcient (LFEC), this paper analyzed the change direction and relative speed of the agricultural labor force and farmland area, and revealed the spatial–temporal coupling characteristics of the agricultural labor force and farmland area in Chongqing. The LFEC refers to the ratio of the change rate of the agricultural labor force to that of farmland area in a certain period of time [39]. The calculation formula is as follows: L −L LCR ij i0 = ij = Li0 LFECij F −F FCRij ij i0 Fi0

In this formula, LFECij represents the LFEC in region i in year j. LCRij and FCRij represent the change rate of the number of agricultural workers and of the farmland area, respectively, in region i in year j. Lij and Fij represent the number of agricultural workers and the farmland area, respectively, in region i in year j. Finally, Li0 and Fi0 represent the number of agricultural workers and farmland area, respectively, in region i in the base year. Based on the LFEC, this paper classiﬁed the coupling of agricultural labor force and farmland area change into the Labor–Farmland Growth Type and the Labor–Farmland Recession Type (Table1).

Table 1. Characteristics of rural labor–farmland elastic.

Type LCR FCR LFEC Characteristics of Rural Labor–Farmland Elastic The growth rate of agricultural labor force is faster Labor–Farmland Recession Type LCR > 0 FCR > 0 LFEC > 1 than that of farmland The growth rate of agricultural labor force is slower Labor–Farmland Growth Type LCR > 0 FCR > 0 0 < LFEC < 1 than that of farmland The agricultural labor force has increased and the Labor–Farmland Recession Type LCR > 0 FCR < 0 LFEC < 0 farmland has decreased The agricultural labor force has decreased and the Labor–Farmland Growth Type LCR < 0 FCR > 0 LFEC < 0 farmland has increased The reduction rate of agricultural labor force is Labor–Farmland Growth Type LCR < 0 FCR < 0 LFEC > 1 faster than that of farmland The reduction rate of agricultural labor force is Labor–Farmland Recession Type LCR < 0 FCR < 0 0 < LFEC < 1 slower than that of farmland

3.2.2. Economy–Labor Elastic Coefﬁcient Using the Economy–Labor Elastic Coefﬁcient (ELEC) [27], this paper analyzed the change direction and relative speed of the agricultural economy and agricultural labor force Sustainability 2021, 13, 8780 6 of 17

and revealed the spatial–temporal coupling characteristics of the agricultural economy and agricultural labor force in Chongqing. The calculation formula is as follows:

E −E ECR ij i0 = ij = Ei0 ELECij L −L LCRij ij i0 Li0

In this formula, ELECij represents the ELEC of region i in year j. ECRij and LCRij represent the change rate of the agricultural economy and of the number of agricultural workers, respectively, of region i in year j. Eij and Lij represent the total agricultural economic output value and the number of agricultural workers, respectively, in region i in year j. Ei0 and Li0 represent the total agricultural economic output value and the number of agricultural workers, respectively, in region i in the base year. Based on the ELEC, this paper divided the coupling of agricultural economic development and the agricultural labor change into the Economy–Labor Growth Type, Economy– Labor Extensive Type, Economy–Labor Intensive Type, Economy–Labor Backward Type, Economy–Labor Decline Type and Economy–Labor Recession Type (Table2).

Table 2. Characteristics of rural economy–labor elastic.

Type ECR LCR ELEC Characteristics of Rural Economy–Labor Elastic The growth rate of agricultural economy is faster Economy–Labor Growth Type ECR > 0 LCR > 0 ELEC > 1 than that of labor force The growth rate of agricultural economy is slower Economy–Labor Extensive Type ECR > 0 LCR > 0 0 < ELEC < 1 than that of labor force The agricultural economy has increased and the Economy–Labor Intensive Type ECR > 0 LCR < 0 ELEC < 0 labor force has decreased The agricultural economy has decreased and the Economy–Labor Backward Type ECR < 0 LCR > 0 ELEC < 0 labor force has increased The reduction rate of agricultural economy is faster Economy–Labor Decline Type ECR < 0 LCR < 0 ELEC > 1 than that of labor force The reduction rate of agricultural economy is Economy–Labor Recession Type ECR < 0 LCR < 0 0 < ELEC < 1 slower than that of labor force

3.2.3. Types of Labor–Farmland–Economy Coupling Based on the division of the Labor–Farmland Elastic Type and the Economy–Labor Elastic Type, the coupling analysis of them was carried out. Labor–Farmland Elastic Type includes the Labor–Farmland Growth Type and the Labor–Farmland Recession Type. Based on the principle of priority of cultivated land protection, types of labor–farmland–economy coupling under the Labor–Farmland Growth Type were divided into 6 types and 1–6 coordination levels preferentially and then types of labor–farmland–economy coupling under the Labor–Farmland Recession Type were divided into 6 types and 2–7 coordination levels. In this study, there were 12 types of labor–farmland–economy coupling in the rural system, which can be divided into seven types of coordination (Table3). The coupling type featuring labor–farmland growth and intensive economy–labor was the best. It is conducive to improving the regional human–land relationship, increasing agricultural productivity, promoting farmers’ income, and promoting rural economic development. However, the coupling of the economy–labor backward type will lead to the insufﬁcient utilization of the rural labor force; thus, hindering the improvement of labor productivity and restricting the development of the rural economy [32]. Both the Economy–Labor Decline Type and the Economy–Labor Recession Type will hinder rural development; there is no doubt that the migration of high-quality agricultural labor to the non-agricultural sectors, along with the outﬂow of agricultural production factors, deserve more attention. Sustainability 2021, 13, 8780 7 of 17

Table 3. Coupling classiﬁcation and characteristics of the rural labor–farmland–economy structure.

Labor–Farmland Elastic Economy–Labor Elastic Types of The Rural Types of Coordination Coefﬁcient Coefﬁcient Labor–Farmland–Economy Coupling Economy–Labor Intensive Type Labor–Farmland Growth Type and 1 High coordination (ECIT) Economy–Labor Intensive Type Economy–Labor Growth Type Labor–Farmland Growth Type and 2 Intermediate coordination (ECGT) Economy–Labor Growth Type Economy–Labor Extensive Type Labor–Farmland Growth Type and 3 Primary coordination Labor–Farmland Growth (ECET) Economy–Labor Extensive Type Type (LFGT) Economy–Labor Backward Type Labor–Farmland Growth Type and 4 On the verge of disorders (ECBT) Economy–Labor Backward Type Economy–Labor Recession Type Labor–Farmland Growth Type and 5 Mild disorders (ECRT) Economy–Labor Recession Type Economy–Labor Decline Type Labor–Farmland Growth Type and 6 Moderate disorders (ECDT) Economy–Labor Decline Type Economy–Labor Intensive Type Labor–Farmland Recession Type and 2 Intermediate coordination (ECIT) Economy–LaborIntensive Type Economy–Labor Growth Type Labor–Farmland Recession Type and 3 Primary coordination (ECGT) Economy–Labor Growth Type Economy–Labor Extensive Type Labor–Farmland Recession Type and 4 On the verge of disorders Labor–Farmland Recession (ECET) Economy–Labor Extensive Type Type (LFRT) Economy–Labor Backward Type Labor–Farmland Recession Type and 5 Mild disorders (ECBT) Economy–Labor Backward Type Economy–Labor Recession Type Labor–Farmland Recession Type and 6 Moderate disorders (ECRT) Economy–Labor Recession Type Economy–Labor Decline Type Labor–Farmland Recession Type and 7 Serious disorders (ECDT) Economy–Labor Decline Type

4. Results 4.1. Spatiotemporal Characteristics of Agricultural Labor Force Change From 2000 to 2010, the average annual rate of the agricultural labor force in Chongqing reduced by 3.86%, and the rate in 20 districts and counties showed a decreasing trend. The reduction rate in Jiangbei District, Dadukou District, Nan’an District, Shapingba District, and Yubei District exceeded 15.00%; the reduction rate in Jiangbei District was as high as 44.83%. The agricultural labor force in 17 districts and counties showed an increasing trend, and the growth rate of Chengkou County, Rongchang District, Kaizhou District, Dianjiang County, and Tongliang District was higher, exceeding 15% (Figure3a). From 2010 to 2018, the average annual reduction rate of the agricultural labor force in Chongqing was 3.56%; the rate in 29 districts and counties showed a decreasing trend. The reduction rate in seven districts and counties exceeded 30.00%, and the rate in Jiangbei District was as high as 71.30%. Only eight districts and counties showed an increasing trend in the agricultural labor force; these districts were mainly concentrated in the northeast of Chongqing (Figure3b) . From 2000 to 2018, the average annual reduction rate of the agricultural labor force in Chongqing was 3.73%, and the agricultural labor force in 25 districts and counties showed a decreasing trend. Among them, Jiangbei District, Dadukou District, Shapingba District, Yubei District, Dazu District, Beibei District, and Changshou District witnessed a reduction rate of over 30.00%; the reduction rate of Jiangbei District was as high as 84.17%. There were 12 districts and counties with increased agricultural labor force, among which Rongchang District, Kaizhou District, Nan’an District, and Dianjiang County registered an increase rate of more than 15.00%, and Nan’an District registered an increase rate of 85.00% (Figure3c). SustainabilitySustainability 20212021,, 1313,, xx 88 ofof 1616

agriculturalagricultural laborlabor forceforce inin ChongqingChongqing waswas 3.73%,3.73%, andand thethe agriculturalagricultural laborlabor forceforce inin 2525 districtsdistricts andand countiescounties showedshowed aa decreasingdecreasing trend.trend. AmongAmong them,them, JiangbeiJiangbei District,District, Dadu-Dadu- koukou District,District, ShapingbaShapingba District,District, YubeiYubei DistrictDistrict,, DazuDazu District,District, BeibeiBeibei District,District, andand Chang-Chang- shoushou DistrictDistrict witnessedwitnessed aa reductionreduction raterate ofof ovoverer 30.00%;30.00%; thethe reductionreduction raterate ofof JiangbeiJiangbei Dis-Dis- tricttrict waswas asas highhigh asas 84.17%.84.17%. ThereThere werewere 1212 districtsdistricts andand countiescounties withwith increasedincreased agricul-agricul- turaltural laborlabor force,force, amongamong whichwhich RongchangRongchang DistDistrict,rict, KaizhouKaizhou District,District, Nan’anNan’an District,District, andand Sustainability 2021, 13, 8780 8 of 17 DianjiangDianjiang CountyCounty registeredregistered anan increaseincrease raterate ofof moremore thanthan 15.00%,15.00%, andand Nan’anNan’an DistrictDistrict registeredregistered anan increaseincrease raterate ofof 85.00%85.00% (Figure(Figure 3c).3c).

Figure 3. (a) Spatial–temporal pattern of agricultural labor force changes in districts of Chongqing Figure 3. (a) Spatial–temporal pattern pattern of of agricultural agricultural la laborbor force force changes changes in in districts districts of of Chongqing Chongqing from 2000 to 2010; (b) Spatial–temporal pattern of agricultural labor force changes in districts of from 2000 to to 2010; 2010; ( (bb)) Spatial–temporal Spatial–temporal pattern pattern of of agricultur agriculturalal labor labor force force changes changes in indistricts districts of of Chongqing from 2010 to 2018; (c) Spatial–temporal pattern of agricultural labor force changes in Chongqing from 2010 2010 to to 2018; 2018; (c (c) )Spatial–temporal Spatial–temporal pattern pattern of of agri agriculturalcultural labor labor force force changes changes in in districtsdistricts ofof ChongqingChongqing fromfrom 20002000 toto 2018.2018. Note:Note: DataData camecame fromfrom ChinaChina StatisticalStatistical YearbookYearbook districts of Chongqing from 2000 to 2018. Note: Data came from China Statistical Yearbook (County (County(County Level)Level) (2001–2019)(2001–2019) andand ChongqingChongqing plplanninganning andand NaturalNatural ResourcesResources Bureau.Bureau. Level) (2001–2019) and Chongqing planning and Natural Resources Bureau. 4.2.4.2. Characteristics Characteristics ofof Spatial–TemporalSpatial–Temporal Coupling CoupCouplingling of ofof the thethe Labor–Farmland–Economy Labor–Farmland–EconomyLabor–Farmland–Economy Structure StructureStructure 4.2.1.4.2.1. Characteristics Characteristics ofof thethe Economy–LaborEconomy–Labor CouplingCoupling TypesTypes FromFrom 20002000 toto 2010,2010, therethere werewere 202020 ECITECITECIT countiescountiescounties ininin ChongqingChongqingChongqing whichwhichwhich werewerewere mainlymainlymainly distributeddistributed inin thethe centralcentral citiescities andand thethe northeastnortheast ofof Chongqing,Chongqing, andand therethere werewere 1717 ECGTECGTECGT countiescounties whichwhich werewere mainlymainlymainly distributeddistributeddistributed inin thethethe connectingconnectingconnecting zonezonezone betweenbetweenbetween QijiangQijiangQijiang DistrictDistrictDistrict andand ChengkouChengkou CountyCounty (Figure(Figure 4 4a).4a).a). FromFromFrom 2010 20102010 to toto 2018, 2018,2018, the thethe number numbernumber of ofofECIT ECITECITcounties countiescountiesin inin ChongqingChongqing increasedincreased toto 25.25. However,However, DadukouDadukou District,District, JiangbeiJiangbei District,District,District, andandand ShapingbaShapingbaShapingba District,District, asas thethe mainmain cities,cities, showedshowed anan ECRTECRTECRT trend,trend,trend, whilewhilewhile Jiulongpo JiulongpoJiulongpo DistrictDistrictDistrict andandand Nan’anNan’anNan’an DistrictDistrict showedshowedshowed the thethe trends trendstrends of ofof ECDT ECDTECDT and andand ECBT, ECBTECBT respectively,, respectivelyrespectively (Figure (Figure(Figure4b). From 4b).4b). FromFrom 2000 to 20002000 2018, toto there2018,2018, weretherethere 22werewere ECIT 2222 counties ECITECIT countiescounties in Chongqing, inin Chongqing,Chongqing, which werewhichwhich mainly werewere mainly distributedmainly distributeddistributed in the central inin thethe citiescentralcentral and citiescities the andand northeast thethe northeastnortheast of Chongqing, ofof Chongqing,Chongqing, and there andand were therethere 11 were ECGTwere 1111 counties. ECGTECGT counties.counties. Dadukou DadukouDadukou District, JiangbeiDistrict,District, District,JiangbeiJiangbei and District,District, Shapingba andand ShapingbaShapingba District, as DistDist therict, mainrict, asas cities, thethe mainmain showed cities,cities, the showed ECRTshowed trend, thethe ECRT whileECRT Nan’antrend,trend, whilewhile District Nan’anNan’an showed DistrictDistrict theECET showshowed trended thethe (Figure ECETECET trend4trendc). (Figure(Figure 4c).4c).

Figure 4. (a) Spatial–temporal pattern of economy–labor of Chongqing from 2000 to 2010; (b) Spatial– temporal pattern of economy–labor of Chongqing from 2010 to 2018; (c) Spatial–temporal pattern of economy–labor of Chongqing from 2000 to 2018. Note: Data came from China Statistical Yearbook (County Level) (2001–2019) and Chongqing planning and Natural Resources Bureau.

The change of the agricultural economy showed typical features. From 2000 to 2010, the growth rate of the agricultural economy of Chongqing registered 137.61%, with an average annual growth rate of 9.04%. The development of the agricultural economy of all counties showed an upward trend. The growth rate of the agricultural economy of the Sustainability 2021, 13, x 9 of 16

Figure 4. (a) Spatial–temporal pattern of economy–labor of Chongqing from 2000 to 2010; (b) Spa- tial–temporal pattern of economy–labor of Chongqing from 2010 to 2018; (c) Spatial–temporal pattern of economy–labor of Chongqing from 2000 to 2018. Note: Data came from China Statistical Yearbook (County Level) (2001–2019) and Chongqing planning and Natural Resources Bureau.

The change of the agricultural economy showed typical features. From 2000 to 2010, Sustainability 2021, 13, 8780 9 of 17 the growth rate of the agricultural economy of Chongqing registered 137.61%, with an average annual growth rate of 9.04%. The development of the agricultural economy of all counties showed an upward trend. The growth rate of the agricultural economy of the centralcentral citiescities andand thethe southeastsoutheast ofof ChongqingChongqing waswas slow.slow. ForFor example,example, thethe growthgrowth raterate ofof ShapingbaShapingba District,District, a a main main city, city, was was only only 8.39%, 8.39%, while while those those of Fulingof Fuling District District and and Wanzhou Wan- Districtzhou District in the newin the districts new districts and Rongchang and Rong Districtchang inDistrict Northeast in Northeast Chongqing Chongqing were 185.56%, were 183.35%,185.56%, and183.35%, 165.41%, and respectively 165.41%, respectively (Figure5a). (Figure From 2010 5a). to From 2018, 2010 Chongqing’s to 2018, Chongqing’s agricultural economyagricultural grew economy by 109.33%, grew withby 109.33%, an average with annual an average growth annual rate ofgrowth 9.67%. rate The of agricultural 9.67%. The economyagricultural of 32economy districts of and 32 districts counties and showed counties a growing showed trend, a growing among trend, which among 26 districts which and26 districts counties and grew counties by more grew than by 100% more and than seven 100% districts and seven and countiesdistricts grewand counties by more grew than 120%.by more Five than districts 120%. withFive adistricts declining with agricultural a declining economy agricultural were economy mainly distributed were mainly in dis- the maintributed cities, in the especially main cities, in Jiangbei especially District in Jiangbei and Dadukou DistrictDistrict, and Dadukou with reduction District, with rates re- of 62.44%duction and rates 34.85%, of 62.44% respectively and 34.85%, (Figure respectively5b). From (Figure 2000 to 2018,5b). From Chongqing’s 2000 to 2018, agricultural Chong- economyqing’s agricultural grew by 397.40%,economy with grew an by average 397.40%, annual with growthan average rate ofannual 9.32%. growth The growth rate of rate9.32%. of sevenThe growth districts rate and of counties seven wasdistricts higher and than counties 420%, amongwas higher which than Wanzhou 420%, Districtamong registeredwhich Wanzhou the highest District growth registered rate ofthe 517.70%. highest growth Dadukou rate District, of 517.70%. Jiangbei Dadukou District, District, and ShapingbaJiangbei District, District, and all Shapingba main cities, District, showed all a downwardmain cities, trend,showed with a downward the reduction trend, rates with of 19.54%,the reduction 18.32%, rates and of 3.16%, 19.54%, respectively 18.32%, and (Figure 3.16%,5c). respectively (Figure 5c).

FigureFigure 5.5. ((aa)) Spatial–temporalSpatial–temporal patternpattern ofof agriculturalagricultural economiceconomic developmentdevelopment ofof ChongqingChongqing fromfrom 20002000 toto 2010; (b) Spatial–temporal patternpattern ofof agricultural economiceconomic developmentdevelopment ofof ChongqingChongqing fromfrom 20102010 toto 2018; (c)) Spatial–temporal patternpattern ofof agriculturalagricultural economiceconomic developmentdevelopment ofof ChongqingChongqing fromfrom 20002000 toto 2018.2018. Note: Data came from China StatisticalStatistical YearbookYearbook (County(County Level)Level) (2001–2019)(2001–2019) andand Chongqing planning and Natural Resources Bureau. Chongqing planning and Natural Resources Bureau.

4.2.2.4.2.2. Characteristics of Labor–Farmland CouplingCoupling FromFrom 20002000 toto 2010,2010, therethere werewere 1414 LFGTLFGT countiescounties inin Chongqing,Chongqing, whichwhich werewere mainlymainly distributeddistributed inin thethe newnew districtsdistricts ofof mainmain citiescities andand thethe southeastsoutheast ofof Chongqing.Chongqing. ThereThere werewere 2323 LFRTLFRT counties,counties, whichwhich werewere mainlymainly distributeddistributed inin thethe centralcentral citiescities andand thethe northeastnortheast ofof ChongqingChongqing (Figure6 6a).a). FromFrom 20102010 toto 2018,2018, the the number number of of LFGT LFGT counties counties in in Chongqing Chongqing increasedincreased toto 24,24, whilewhile thethe numbernumber ofof LFRTLFRT countiescounties decreaseddecreased toto 1313 (Figure(Figure6 6b).b). From From 2000 2000 toto 2018, there there were were 19 19 LFGT LFGT counties counties in in Chongqing, Chongqing, which which were were mainly mainly distributed distributed in the in thenew new districts districts of main of main cities cities and the and northeast the northeast of Chongqing, of Chongqing, and there and therewere 18 were LFRT 18 LFRTcoun- countiesties (Figure (Figure 6c). 6c). It also showed spatial–temporal change in farmland. From 2000 to 2010, the average annual reduction rate of farmland area in Chongqing was 0.32%, showing a decreasing trend in 26 districts and counties. The reduction rate of farmland area in Nan’an District, Dadukou District, Shapingba District, Jiangbei District, Jiulongpo District, and Banan District exceeded 30%. The farmland area of 11 districts and counties showed an increasing trend, and the increase rate of Pengshui Miao and Tujia Autonomous County, Tongnan District, Qijiang District, and Qianjiang District exceeded 15% (Figure7a). From 2010 to 2018, the average annual reduction rate of farmland area in Chongqing was 0.36%, and the farmland area in 33 districts and counties showed a decreasing trend. The farmland area reduction rate in Jiangjin District, Jiangbei District, Dadukou District, Nan’an District, and Jiulongpo District exceeded 30%; only Qianjiang District, Liangping District, Wanzhou Sustainability 2021, 13, x 10 of 16

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District, and Xiushan Tujia and Miao Autonomous County showed an increasing trend in farmland area (Figure7b). From 2000 to 2018, the average annual reduction rate of

farmland area in Chongqing was 0.34%, and the farmland area in 29 districts and counties showedFigure 6. a(a) decreasing Spatial–temporal trend. pattern The reductionof labor–farmland rate of of farmland Chongqing area from in 2000 Dadukou to 2010; District, (b) Spa- Jiangbeitial–temporal District, pattern Nan’an of labor–farmland District, and of Jiulongpo Chongqing District from 2010 in the to 2018; central (c) citiesSpatial–temporal exceeded 60%, pattern of labor–farmland of Chongqing from 2000 to 2018. Note: Data came from China Statistical and the reduction rates in Chengkou County, Wushan County, and Fengdu County in the Yearbook (County Level) (2001–2019) and Chongqing planning and Natural Resources Bureau. northeast of Chongqing were 30.61%, 16.51%, and 24.63%, respectively. Eight counties with an increased farmland area were mainly distributed in the southeast and northeast of It also showed spatial–temporal change in farmland. From 2000 to 2010, the average Sustainability 2021, 13, x Chongqing, and Pengshui Miao and Tujia Autonomous County registered an increase10 of rate 16 annual reduction rate of farmland area in Chongqing was 0.32%, showing a decreasing of over 30% in farmland (Figure7c). trend in 26 districts and counties. The reduction rate of farmland area in Nan’an District, Dadukou District, Shapingba District, Jiangbei District, Jiulongpo District, and Banan Dis- trict exceeded 30%. The farmland area of 11 districts and counties showed an increasing trend, and the increase rate of Pengshui Miao and Tujia Autonomous County, Tongnan District, Qijiang District, and Qianjiang District exceeded 15% (Figure 7a). From 2010 to 2018, the average annual reduction rate of farmland area in Chongqing was 0.36%, and the farmland area in 33 districts and counties showed a decreasing trend. The farmland area reduction rate in Jiangjin District, Jiangbei District, Dadukou District, Nan’an Dis- trict, and Jiulongpo District exceeded 30%; only Qianjiang District, Liangping District, Wanzhou District, and Xiushan Tujia and Miao Autonomous County showed an increasing trend in farmland area (Figure 7b). From 2000 to 2018, the average annual reduction rate of farmland area in Chongqing was 0.34%, and the farmland area in 29 districts and counties showed a decreasing trend. The reduction rate of farmland area in Dadukou Dis- trict, Jiangbei District, Nan’an District, and Jiulongpo District in the central cities exceeded Figure60%,Figure and 6.6. ((a athe)) Spatial–temporalSpatial–temporal reduction rates pattern pattern in Chengkou of of labor–farmland labor–farmland County, of Wushanof Chongqing Chongqing County, from from 2000 and 2000 to Fengdu 2010;to 2010; (b) County Spatial–(b) Spa- temporalintial–temporal the northeast pattern pattern of of labor–farmland Chongqing of labor–farmland were of Chongqing 30.61%, of Chongqing 16.51%, from 2010from and to2010 24.63%, 2018; to (2018;c) Spatial–temporalrespectively. (c) Spatial–temporal Eight pattern coun- pat- of tern of labor–farmland of Chongqing from 2000 to 2018. Note: Data came from China Statistical labor–farmlandties with an increased of Chongqing farmland from area 2000 towere 2018. mainly Note: Datadistributed came from in the China southeast Statistical and Yearbook north- Yearbook (County Level) (2001–2019) and Chongqing planning and Natural Resources Bureau. (Countyeast of Chongqing, Level) (2001–2019) and Pengshui and Chongqing Miao planningand Tujia and Autonomous Natural Resources County Bureau. registered an increase rate of over 30% in farmland (Figure 7c). It also showed spatial–temporal change in farmland. From 2000 to 2010, the average annual reduction rate of farmland area in Chongqing was 0.32%, showing a decreasing trend in 26 districts and counties. The reduction rate of farmland area in Nan’an District, Dadukou District, Shapingba District, Jiangbei District, Jiulongpo District, and Banan Dis- trict exceeded 30%. The farmland area of 11 districts and counties showed an increasing trend, and the increase rate of Pengshui Miao and Tujia Autonomous County, Tongnan District, Qijiang District, and Qianjiang District exceeded 15% (Figure 7a). From 2010 to 2018, the average annual reduction rate of farmland area in Chongqing was 0.36%, and the farmland area in 33 districts and counties showed a decreasing trend. The farmland area reduction rate in Jiangjin District, Jiangbei District, Dadukou District, Nan’an Dis- trict, and Jiulongpo District exceeded 30%; only Qianjiang District, Liangping District, Wanzhou District, and Xiushan Tujia and Miao Autonomous County showed an increasing trend in farmland area (Figure 7b). From 2000 to 2018, the average annual reduction

rate of farmland area in Chongqing was 0.34%, and the farmland area in 29 districts and Figurecounties 7. (showeda) Spatial–temporal a decreasing pattern trend. of The farmland reduction area rate change of farmland of Chongqing area fromin Dadukou 2000 to 2010; Dis- (trict,b) Spatial–temporal Jiangbei District, pattern Nan’an of farmland District, area and change Jiulongpo of Chongqing District in from the 2010central to 2018;cities ( cexceeded) Spatial– temporal60%, and pattern the reduction of farmland rates area in Chengkou change of ChongqingCounty, Wushan from 2000 County, to 2018. and Note: Fengdu Data County came fromin the China northeast Statistical of Chongqing Yearbook (County were 30.61%, Level) (2001–2019) 16.51%, and and 24.63%, Chongqing respectively. planning andEight Natural coun- Resourcesties with Bureau.an increased farmland area were mainly distributed in the southeast and north- 4.2.3.east of Characteristics Chongqing, and of the Pengshui Rural Labor–Farmland–Economy Miao and Tujia Autonomous Coupling County registered an increase rate of over 30% in farmland (Figure 7c). There are seven types of rural labor–farmland–economy coupling in each district or county of Chongqing, among which, from 2000 to 2010, the spatial pattern characteristics of the rural labor–farmland–economy coupling were demonstrated as high coordination, intermediate coordination, and primary coordination. The numbers of counties in these three groups were 10, 14, and 13, respectively (Figure8a). From 2010 to 2018, the spa-

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Figure 7. (a) Spatial–temporal pattern of farmland area change of Chongqing from 2000 to 2010; (b) Spa- tial–temporal pattern of farmland area change of Chongqing from 2010 to 2018; (c) Spatial–temporal pattern of farmland area change of Chongqing from 2000 to 2018. Note: Data came from China Statistical Yearbook (County Level) (2001–2019) and Chongqing planning and Natural Resources Bureau.

4.2.3. Characteristics of the Rural Labor–Farmland–Economy Coupling There are seven types of rural labor–farmland–economy coupling in each district or county of Chongqing, among which, from 2000 to 2010, the spatial pattern characteristics Sustainability 2021, 13, 8780 11 of 17 of the rural labor–farmland–economy coupling were demonstrated as high coordination, intermediate coordination, and primary coordination. The numbers of counties in these three groups were 10, 14, and 13, respectively (Figure 8a). From 2010 to 2018, the spatial tialpattern pattern characteristics characteristics of the of therural rural labor–fa labor–farmland–economyrmland–economy coupling coupling were were divided divided into intofive ﬁvetypes: types: high high coordination, coordination, intermediate intermediate coordination, coordination, primary primary coordination, coordination, mild mild dis- disorders,orders, and and serious serious disorders. disorders. Among Among them, them, the thenumber number of counties of counties with with high high coordina- coor- dinationtion increased increased to 20, to while 20, while the thenumber number of co ofunties counties with with intermediate intermediate coordination coordination and andprimary primary coordination coordination decreased decreased significantly; signiﬁcantly; however, however, the central the central cities cities showed showed a state a stateof disorder of disorder (Figure (Figure 8b). 8Fromb). From 2000 2000 to 2018, to 2018, the spatial the spatial pattern pattern characteristics characteristics of the of rural the rurallabor–farmland–economy labor–farmland–economy coupling coupling were weredivided divided into six into types: six types: high coordination, high coordination, inter- intermediatemediate coordination, coordination, primary primary coordination, coordination, on on the the verge verge of of disorders, disorders, mild mild disorders,disorders, andand moderatemoderate disorders.disorders. AmongAmong them,them, thethe numbersnumbers ofof countiescounties withwith highhigh coordination,coordination, intermediateintermediate coordination, coordination, and and primary primary coordination coordination were were 16, 7,16, and 7, 10,and respectively. 10, respectively. Shap- ingbaShapingba District, District, Dadukou Dadukou District, Dist Jiangbeirict, Jiangbei District, District, and Nan’an and Na District,n’an District, as the mainas the cities, main werecities, regarded were regarded as out ofas orderout of (Figure order (Figure8c). 8c).

FigureFigure 8.8. ((aa)) Spatial–temporalSpatial–temporal patternpattern ofof labor–farmland–economylabor–farmland–economy ofof ChongqingChongqing fromfrom 20002000 toto 2010;2010; ((bb)) Spatial–temporalSpatial–temporal patternpattern ofof labor–farmland–economylabor–farmland–economy ofof ChongqingChongqing fromfrom 20102010 toto 2018;2018; ((cc)) (c)(c) Spatial–temporal pattern of labor–farmland–economy of Chongqing from 2000 to 2018. Note: Data Spatial–temporal pattern of labor–farmland–economy of Chongqing from 2000 to 2018. Note: Data came from China Statistical Yearbook (County Level) (2001–2019) and Chongqing planning and came from China Statistical Yearbook (County Level) (2001–2019) and Chongqing planning and Natural Resources Bureau. Natural Resources Bureau. According to the spatial–temporal coupling types, from 2000 to 2018, the districts and According to the spatial–temporal coupling types, from 2000 to 2018, the districts counties featuring high coordination accounted for the largest proportion in the coordi- and counties featuring high coordination accounted for the largest proportion in the nation types of spatial–temporal coupling in the rural labor–farmland–economy structure. coordination types of spatial–temporal coupling in the rural labor–farmland–economy structure.During the During period thefrom period T1 to fromT2, the T1 proporti to T2, theon of proportion counties featuring of counties high featuring coordination high coordinationincreased by increased 27.03%, those by 27.03%, featuring those mild featuring disorders mild increased disorders by increased 10.81%, by and 10.81%, thoseand fea- thoseturing featuring serious disorders serious disorders increased increased by 2.70%. by 2.70%.The proportion The proportion of counties of counties featuring featuring inter- intermediatemediate coordination coordination decreased decreased by 21.62% by 21.62% and and those those featuring featuring primary primary coordination coordination de- decreasedcreased by by 18.92%. 18.92%. The The counties counties that that transf transformedormed from intermediate coordinationcoordination andand primaryprimary coordinationcoordination toto highhigh coordinationcoordination accountedaccounted forfor 21.62%21.62% andand 16.22%, respectively, inin allall countiescounties (Table(Table4 ).4).

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Table 4. Transformation characteristics of coupling types in the labor–farmland–economy structure.

T2 T1 High Coordination Intermediate Primary On The Verge of Mild Disorders Moderate Disorders Serious Disorders Reduction (%) Coordination (%) Coordination (%) Disorders (%) (%) (%) (%) (%) High coordination (%) 16.22 2.70 5.41 0.00 2.70 0.00 0.00 10.81 Intermediate Coordination (%) 21.62 0.00 5.41 0.00 8.11 0.00 2.70 37.84 Primary Coordination (%) 16.22 13.51 5.41 0.00 0.00 0.00 0.00 29.73 On The Verge of Disorders (%) 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Mild Disorders (%) 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Moderate Disorders (%) 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Serious Disorders (%) 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 New Increment 37.84 16.22 10.81 0.00 10.81 0.00 2.70 Net Growth 27.03 −21.62 −18.92 0.00 10.81 0.00 2.70 Note: “New increment” means the difference between the percentage of the number of counties of each type in the total number of counties in this study during the time period of T2 and the percentage of such unchanged counties in the total number of counties in this study during the time period of T1–T2. “Decrement” means the difference between the percentage of the number of counties of each type in the total number of counties in this study during the time period of T1 and the percentage of such unchanged counties of this type in the total number of counties in this study during the time period of T1–T2. The net growth refers to the difference between the new increment and the decrement. Sustainability 2021, 13, 8780 13 of 17

5. Discussion For much of its history, China was a large, traditional, and agricultural country. Since the reform and opening up was initiated, talent, land, capital, and other resources in rural areas have rapidly ﬂowed to cities, making great contributions to China’s rapid economic development. However, problems such as “hollowing” villages and abandoned land have become increasingly serious [8]. The relationship between farmers and land has also undergone a fundamental change because of rapid urbanization [40]. Young and middle-aged farmers as well as educated farmers took the lead in entering cities. After obtaining stable, high-income jobs, they brought their children and other family members to reside in cities [41]; thus, resulting in a decline in the rural population and a shortage of labor there. From 2000 to 2018, the agricultural labor force in Chongqing showed a decreasing trend, especially in the central cities (Figure3), which was related to the rapid economic development, more employment opportunities, and a greater attraction to farmers there. Since the targeted poverty alleviation policy was adopted, poverty alleviation by means of developing industries has gradually expanded. This has provided more jobs to rural residents, especially the poor left behind [42], and it has drawn some outsiders to the countryside to become involved in the agricultural economy. Therefore, the agricultural labor force in some regions of the southeast and northeast of Chongqing increased (Figure3). In the process of rapid urbanization, the problems of the non-agricultural use of agricultural land related to infrastructure construction the development of enterprises, industry, and commerce and community construction have been intensiﬁed; thus, resulting in the gradual reduction or even the complete loss of farmland in some villages [8]. The transfer of labor force between urban and rural areas has also changed the way in which farmers use farmland [43]. Young and middle-aged laborers are unwilling to return home to farm after obtaining a job in the city, and they have transferred their farmland to other villagers or abandoned it [14,18]. However, some studies have shown that the transfer of agricultural labor force is conducive to the transfer of farmland and large-scale operation and promotes industrial development [14,16]. “Amphibious people” in both urban and rural areas have also accelerated the problem of farmland being converted for non-agricultural purposes. Migrant workers return to their country homes during busy farming seasons or holidays, and use the funds earned from their non-agricultural work to repair their houses, and even expand their living space there [44]. At the same time, as the rural economy developed, some urban people went to the countryside to start businesses, bring along with them capital, technology, and resources. From 2000 to 2018, the farmland area of 78.38% counties in Chongqing showed a downward trend. This trend is most prominent in the central cities and the new districts of the main cities (Figure5) . Since China’s Western Development Program was initiated, the central cities and the new districts of the main cities have created key development advantages in Chongqing, turned into a growth pole of high-quality development for the future, and became one of the major engines of the Chengdu–Chongqing Economic Circle. Its dependence on new city construction, industrial cluster cultivation, and public facilities allocation for farmland was higher than other regions. The remediation projects for degraded, empty, and waste land and the policies for poverty alleviation in association with land use could not only supplement farmland resources, but provide high-standard farmland and agricultural development models for agricultural production [45,46]. The southeast of Chongqing and the northeast of Chongqing are the key areas for implementing the policy of “balancing the occupation and supplementation of farmland.” The land remediation projects related to rural homestead reclamation and wasteland reclamation suitable for agriculture continued; thus, effectively supplementing the area of farmland. From 2000 to 2018, the degree of coupling and coordination of human, land and industry in poverty-stricken counties of Chongqing is gradually becoming better, and the degree of coupling and coordination of human, land and industry in central urban area is gradually becoming worse (Figure6). Among the 14 national poverty-stricken counties Sustainability 2021, 13, 8780 14 of 17

in Chongqing, the rural labor–farmland–economy coupling type in 11 counties showed a trend of gradual coordinated change. The reason is that during the period of targeted poverty alleviation, the creation of job opportunities had effectively promoted the transfer of the agricultural labor force. The development of relevant industries and financial ser- vices had encouraged and driven a large portion of the poor population to participate in the development of such industries and make efficient use of farmland. This improved the scale and intensification of farmland utilization and enhanced the agricultural economic aggregate and efficiency. In the future, Chongqing should focus on industrial development, introduce high-caliber talent, improve the interest-based mechanism in the agricultural industry, upgrade the quality of leading industries, promote the development of rural areas and agriculture, and effectively facilitate rural revitalization. There were five districts in the central cities where the coupling and coordination degree of labor–farmland–economy gradually decreased, accounting for 50% of the total decreasing counties. The occupation of farmland due to rapid urbanization led to the transfer of the agricultural labor force in the central cities (Figure3), a decline of farmland area (Figure4), and a decrease in the total agricultural economic aggregate (Figure4). In the future, it will be necessary to increase the transfer of the agricultural population and promote the transformation of farmers into citizens by providing them with jobs in the central cities. In particular, Chongqing should vigorously develop the tertiary industry to enhance the value of the agricultural industry and promote the integration and development of both urban and rural areas. In addition, Wuxi County, Fengjie County, Qianjiang District, Kaizhou District, and Yongchuan District featured a lower-level rural labor–farmland–economy coordination (Figure6). This was mainly manifested in the decrease in farmland and the increase in the agricultural labor force, and the insufficient development of the agricultural economy, the low-level mechanization in the remote rural areas, and the difficulty of farming with a labor force consisting of mainly older and disabled workers [47]. As a result, they lacked sufficient management in farmland which led to low efficiency. During the period when the targeted poverty alleviation effectively facilitates rural revitalization, Chongqing kept protecting farmland and transferring agricultural labor. Qianjiang District in the southeast of Chongqing strove to improve the efficiency of farmland use and the agricultural industrial benefits, and moderately increased the transfer of agricultural labor. It is worth noting that under the influence of policies such as returning farmland to forests and ecological protection, Chengkou County, Wushan County, and Fengdu County in the northeast of Chongqing had become the most prominent in the decrease in farmland, and the rural labor–farmland–economy coupling and coordination there was becoming better. In the future, Chongqing should keep making full use of resources of green water and green mountains and realize the coordinated rural labor–farmland–economy development by adhering to the development concept of “ecological industrialization” such as organic agriculture, ecological agriculture and eco-tourism.

6. Conclusions Using the cross-sectional data of the agricultural labor force, agricultural economy, and farmland area in Chongqing in 2000, 2010, and 2018, this paper discussed the spatial– temporal coupling relationship between the agricultural labor force and agricultural economy, and between the agricultural labor force and farmland. This provided theoretical and methodical support for the coordinated development of human and land industries in different regions. From the perspective of rural labor, farmland, and economy in the development of the rural system, this paper researched the spatial–temporal characteristics of the rural labor–farmland–economy coupling in different districts and counties of Chongqing by studying the changes of three factors: agricultural labor force, agricultural economy, and farmland area. The results showed that, from 2000 to 2018, the number of agricultural workers in Chongqing decreased by 49.53%, and the reduction rate was highest in the central cities. The growth rate of the agricultural economy in Chongqing was 397.4%; Sustainability 2021, 13, 8780 15 of 17

the growth trend in the northeast of Chongqing was the highest; the growth rate in the main cities was relatively slow. The farmland area in 29 districts and counties showed a decreasing trend, while that in 8 districts and counties showed an increasing trend, and the farmland area in the main cities decreased the fastest. There are 16 districts and counties (43.24% of the total) in Chongqing whose rural labor–farmland–economy coupling type has been regarded as the Labor–Farmland Growth Type and the Economy–Labor Intensive Type. They are mainly distributed in the northeast of Chongqing and the new districts in main cities. The coupling types in all districts and counties in association with the change of the agricultural labor force and the development of the agricultural economy and farmland have developed in a benign direction as a whole. In the context of rural revitalization in the future and under the combined action of the endogenous driving force for rural development and the external driving force for development in cities, there will occur a change to the rural labor–farmland–economy structure. It is essential to attract talent to rural development and construction, to protect the quantity and quality of farmland, to promote the upgrading of the agriculture-related industrial structure, and to enhance development vitality in rural areas. This has become the key to consolidating the achievements of poverty alleviation and promoting rural revitalization and sustainable development. In the future, it should strengthen research on the Labor–Farmland Elastic Coefficient, the minimum average arable land area per agricultural worker, and the threshold of the ELEC in its different areas. This will be of important guiding significance for promoting the flow of urban and rural talents, intensive land management, and the rapid development of the agricultural economy. In sum, it will support rural revitalization and urban–rural integration.

Author Contributions: Methodology, L.Z.; validation, L.Z. and H.L.; formal analysis, L.Z. and M.Y.; data curation, W.L. and H.H.; writing—review and editing, L.Z., M.Y., W.L., and H.L.; visualization, H.H.; project administration, L.Z. and H.L.; funding acquisition, L.Z. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by The Social Science Planning Project of Chongqing in 2019, 2019YBGL076; the Chongqing Technology Foresight and Institutional Innovation Project, cstc2020jsyj- zzysbAX0077; The Open Fund of the Key Laboratory of Analysis and Simulation of Regional Sustainable Development by the Chinese Academy of Sciences, KF2020-01; postdoctoral (No. 145316) research. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: (1) A publicly available dataset was analyzed in this study. These data can be found here: (http://tjj.cq.gov.cn/ (accessed on 7 October 2020)). The National Bureau of Statistics, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, and 2019. China Statistical Yearbook (County Level). (2) Data were obtained from the Chongqing planning and the Natural Resources Bureau and are available from the authors with the permission of the Chongqing planning and Natural Resources Bureau. Conﬂicts of Interest: The authors declare no conﬂict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References 1. Liu, Y. The basic theory and methodology of rural revitalization planning in China. Acta Geogr. Sin. 2020, 75, 1120–1133. (In Chinese) 2. Long, H.; Liu, Y.; Li, X.; Chen, Y. Building new countryside in China: A geographical perspective. Land Use Policy 2010, 27, 457–470. [CrossRef] 3. Rigg, J.; Salamanca, A.; Thompson, E.C. The puzzle of East and Southeast Asia’s persistent smallholder. J. Rural Stud. 2016, 43, 118–133. [CrossRef] 4. Liu, Y. Research on the urban-rural integration and rural revitalization in the new era in China. Acta Geogr. Sin. 2018, 73, 637–650. (In Chinese) Sustainability 2021, 13, 8780 16 of 17

5. Yang, Y.; Liu, Y.; Li, Y.; Li, J. Measure of urban-rural transformation in Beijing-Tianjin-Hebei region in the new millennium: Population-land-industry perspective. Land Use Policy 2018, 79, 595–608. [CrossRef] 6. Marrit Van Den Berg, M.; Hengsdijk, H.; Wolf, J.; Van Ittersum, M.K.; Wang, G.; Roetter, R.P. The impact of increasing farm size and mechanization on rural income and rice production in Zhejiang province, China. Agric. Syst. 2007, 94, 841–850. [CrossRef] 7. Liu, G.; Wang, H.; Cheng, Y.; Zheng, B.; Lu, Z. The impact of rural out-migration on arable land use intensity: Evidence from mountain areas in Guangdong, China. Land Use Policy 2016, 59, 569–579. [CrossRef] 8. Liu, Y.; Fang, F.; Li, Y. Key issues of land use in China and implications for policy making. Land Use Policy 2014, 40, 6–12. [CrossRef] 9. Wang, Y.; Wen, Q.; Liu, Y. Achieving effective connection between rural revitalization and targeted poverty alleviation in poverty-stricken regions. Sci. Geogr. Sin. 2020, 40, 1840–1847. 10. Liu, Y.; Li, Y. Revitalize the world’s countryside. Nature 2017, 548, 275–277. [CrossRef] 11. Cheng, M.; Liu, Y.; Jiang, N. Study on the spatial pattern and mechanism of rural population-land-industry coordinating development in Huang-Huai-Hai Area. Acta Geogr. Sin. 2019, 74, 1576–1589. (In Chinese) 12. Lewis, A. Duality Economy Theory; Beijing University of Economics Press: Beijing, China, 1989. 13. Ibrahim, S.; Osama, E. Impact of technological changes and economic liberalization on agricultural labor employment and Productivity. Contemp. Egypt 1996, 8, 3–18. 14. Deininger, K.; Jin, S. The potential of land rental markets in the process of economic development: Evidence from China. J. Dev. Econ. 2005, 78, 241–270. [CrossRef] 15. Ma, Z.; Zhang, W.; Liang, Z.; Cui, H. Labour migration as a new determinant of income growth in rural China. Popul. Res. 2004, 28, 2–10. 16. Gao, J.; Song, G. Impact of Rural Labor Transfer Scale on Farmland Transfer. Econ. Gerogr. 2020, 40, 172–178. 17. Lieskovský, J.; Bezák, P.; Špulerová, J.; Lieskovský, T.; Koleda, P.; Dobrovodská, M.; Burgi, M.; Gimmi, U. The abandonment of traditional agricultural landscape in Slovakia—Analysis of extent and driving forces. J. Rural Stud. 2015, 37, 75–84. [CrossRef] 18. Xu, D.; Deng, X.; Guo, S.; Liu, S. Labor migration and farmland abandonment in rural China: Empirical results and policy implications. J. Environ. Manag. 2018, 232, 738–750. [CrossRef] 19. Gao, T.M.; Anna, L.; Vasilii, Y. Sustainable Rural Development in Northern China: Caught in a Vice between Poverty, Urban Attractions, and Migration. Sustainability 2018, 10, 1467. 20. Liao, L.W.; Long, H.L.; Ma, E.P. Rural Labor Change and Farmland Use Transition. Econ. Geogr. 2021, 41, 148–155. (In Chinese) 21. Qu, Y.B.; Zhao, L.J.; Chai, Y.F.; Li, Y.F.; Zhu, W.Y.; Ping, Z.L. Multidimensional form identification and targeted governance of hollow villages from the rural revitalization perspective: Taking Fangsi Town of Yucheng City in Shangdong Province as an example. Resour. Sci. 2021, 43, 776–789. (In Chinese) 22. Ma, L.; Long, H.L.; Zhang, Y.N.; Tu, S.S.; Ge, D.Z. Spatio-temporal coupling relationship between agricultural labor changes and agricultural economic development at county level in China and its implications for rural revitalization. Acta Geogr. Sin. 2018, 73, 2364–2377. (In Chinese) 23. Yang, M.N.; Zhang, Y.; Yang, Q.S.; Liu, J.; Huang, F. Coupling Relationship between Agricultural Labor and Agricultural Production Against the Background of Rural Shrinkage: A Case Study of Songnen Plain, China. Sustainability 2019, 11, 5804. [CrossRef] 24. Brown, C.; Lava, P.Y.; Zhang, J.; Zhouma, D.Q. Sustainability of Agricultural Diversity in the Farm Households of Southern Tibet. Sustainability 2019, 11, 5756. [CrossRef] 25. Lu, H.; Xie, H.; Yao, G. Impact of land fragmentation on marginal productivity of agricultural labor and non-agricultural labor supply: A case study of Jiangsu, China. Habitat Int. 2019, 83, 65–72. [CrossRef] 26. Feng, S. Land rental, off-farm employment and technical efficiency of farm households in Jiangxi Province, China. NJAS Wagening. J. Life Sci. 2008, 55, 363–378. [CrossRef] 27. Ma, L.; Long, H.; Zhang, Y.; Tu, S.; Ge, D.; Tu, X. Agricultural labor changes and agricultural economic development in China and their implications for rural vitalization. J. Geogr. Sci. 2019, 29, 163–179. [CrossRef] 28. Robson, J.P.; Berkes, F. Exploring some of the myths of land use change: Can rural to urban migration drive declines in biodiversity? Glob. Environ. Chang. 2011, 21, 844–854. [CrossRef] 29. Gollin, D.; Parente, S.; Rogerson, R. The role of agriculture in development. Am. Econ. Rev. 2002, 92, 160–164. [CrossRef] 30. Sherlund, S.M.; Barrett, C.B.; Adesina, A.A. Smallholder technical efficiency controlling for environmental production conditions. J. Dev. Econ. 2002, 69, 85–101. [CrossRef] 31. Eberhardt, M.; Vollrath, D. The effect of agricultural technology on the speed of development. World Dev. 2016, 109, 483–496. [CrossRef] 32. Long, H.L.; Tu, S.S.; Ge, D.Z.; Li, T.T.; Liu, Y.S. The allocation and management of critical resources in rural China under restructuring: Problems and prospects. J. Rural Stud. 2016, 47, 392–412. [CrossRef] 33. Guo, Y.; Zhou, Y.; Han, Y. Population aging in rural China: Spatial-temporal pattern and countermeasures for rural revitalization. Geogr. Res. 2019, 38, 667–683. (In Chinese) 34. Ge, D.Z.; Long, H.L.; Zhang, Y.N.; Tu, S.S. Analysis of the coupled relationship between grain yields and agricultural labor changes in China. J. Geogr. Sci. 2018, 28, 93–108. [CrossRef] 35. Kyle, E. Agricultural productivity and the sectoral reallocation of labor in rural India. J. Dev. Econ. 2018, 135, 488–503. Sustainability 2021, 13, 8780 17 of 17

36. Zhou, Y.; Guo, Y.; Liu, Y. Areal types and their development paths in rural China. Geogr. Res. 2019, 38, 467–481. (In Chinese) 37. Zhang, H. Research on Rural Labor Transfer under the Background of Urban-Rural Development in Chongqing; Southeast University: Chongqing, China, 2011. 38. Yu, F. The Effects of the Rural Labor Transfer on Agricultural Production in Chongqing—Based on the Investigation of 402 Peasant Households in Chongqing; Sichuan Agricultural University: Chengdu, China, 2013. 39. Liu, Y.; Li, Y. Spatio-temporal coupling relationship between farmland and agricultural labor changes at county level in China. Acta Geogr. Sin. 2010, 65, 1602–1612. (In Chinese) 40. Wang, Y.H.; Xin, L.J.; Zhang, H.Z.; Li, Y.Q. An Estimation of the Extent of Rent-Free Farmland Transfer and Its Driving Forces in Rural China: A Multilevel Logit Model Analysis. Sustainability 2019, 11, 3161. [CrossRef] 41. Chen, R.; Ye, C.; Cai, Y.; Xing, X.; Chen, Q. The impact of rural out-migration on land use transition in China: Past, present and trend. Land Use Policy 2014, 40, 101–110. [CrossRef] 42. Wang, Y.; Li, Y. Promotion of degraded land consolidation to rural poverty alleviation in the agro-pastoral transition zone of northern China—Science Direct. Land Use Policy 2019, 88, 104114. [CrossRef] 43. Xu, D.; Yong, Z.; Deng, X.; Zhuang, L.; Qing, C. Rural-urban migration and its effect on land transfer in rural China. Land 2020, 9, 81. [CrossRef] 44. Fu, C.; Liu, Y. Coordinated development between land use change and population change in urbanizing China. Econ. Geogr. 2013, 33, 47–51. (In Chinese) 45. Liu, Y.; Wang, Y. Rural land engineering and poverty alleviation: Lessons from typical regions of China. J. Geogr. Sci. 2019, 29, 643–657. [CrossRef] 46. Wang, Y.; Liu, Y. New material for transforming degraded sandy land into productive farmland. Land Use Policy 2020, 92, 104477. [CrossRef] 47. Yu, Y.; Xu, T.; Wang, T. Outmigration drives cropland decline and woodland increase in rural regions of southwest China. Land 2020, 9, 443. [CrossRef]